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Demand Response Economic Assessment with the Integration of Renewable Energy for Developing Electricity Markets

Author

Listed:
  • Abdul Conteh

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
    Electricity Distribution and Supply Authority (EDSA), Freetown 00232, Sierra Leone)

  • Mohammed Elsayed Lotfy

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
    Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt)

  • Oludamilare Bode Adewuyi

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan)

  • Paras Mandal

    (Department of Electrical and Computer Engineering, University of Texas, El Paso, TX 79968, USA)

  • Hiroshi Takahashi

    (Fuji Elctric Co., Ltd., Tokyo 141-0032, Japan)

  • Tomonobu Senjyu

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan)

Abstract

Electricity disparity in sub-Saharan Africa is a multi-dimensional challenge that has significant implications on the current socio-economic predicament of the region. Strategic implementation of demand response (DR) programs and renewable energy (RE) integration can provide efficient solutions with several benefits such as peak load reduction, grid congestion mitigation, load profile modification, and greenhouse gas emissions reduction. In this research, an incentive and price-based DR programs model using the price elasticity concepts is proposed. Economic analysis of the customer benefit, utility revenue, load factor, and load profile modification are optimally carried out using Freetown (Sierra Leone) peak load demand. The strategic selection index is employed to prioritize relevant DR programs that are techno-economically beneficial for the independent power producers (IPPs) and participating customers. Moreover, optimally designed hybridized grid-connected RE was incorporated using the Genetic Algorithm (GA) to meet the deficit after DR implementation. GA is used to get the optimal solution in terms of the required PV area and the number of BESS to match the net load demand after implementing the DR schemes. The results show credible enhancement in the load profile in terms of peak period reduction as measured using the effective load factor. Moreover, customer benefit and utility revenues are significantly improved using the proposed approach. Furthermore, the inclusion of the hybrid RE supply proves to be an efficient approach to meet the load demand during low peak and valley periods and can also mitigate greenhouse gas emissions.

Suggested Citation

  • Abdul Conteh & Mohammed Elsayed Lotfy & Oludamilare Bode Adewuyi & Paras Mandal & Hiroshi Takahashi & Tomonobu Senjyu, 2020. "Demand Response Economic Assessment with the Integration of Renewable Energy for Developing Electricity Markets," Sustainability, MDPI, vol. 12(7), pages 1-20, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2653-:d:337880
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    References listed on IDEAS

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    Cited by:

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    2. Mahmoud M. Gamil & Makoto Sugimura & Akito Nakadomari & Tomonobu Senjyu & Harun Or Rashid Howlader & Hiroshi Takahashi & Ashraf M. Hemeida, 2020. "Optimal Sizing of a Real Remote Japanese Microgrid with Sea Water Electrolysis Plant Under Time-Based Demand Response Programs," Energies, MDPI, vol. 13(14), pages 1-22, July.
    3. Keifa Vamba Konneh & Hasan Masrur & Mohammad Lutfi Othman & Hiroshi Takahashi & Narayanan Krishna & Tomonobu Senjyu, 2021. "Multi-Attribute Decision-Making Approach for a Cost-Effective and Sustainable Energy System Considering Weight Assignment Analysis," Sustainability, MDPI, vol. 13(10), pages 1-22, May.
    4. Larry Erickson & Stephanie Ma, 2021. "Solar-Powered Charging Networks for Electric Vehicles," Energies, MDPI, vol. 14(4), pages 1-10, February.
    5. Mark Kipngetich Kiptoo & Oludamilare Bode Adewuyi & Masahiro Furukakoi & Paras Mandal & Tomonobu Senjyu, 2023. "Integrated Multi-Criteria Planning for Resilient Renewable Energy-Based Microgrid Considering Advanced Demand Response and Uncertainty," Energies, MDPI, vol. 16(19), pages 1-25, September.
    6. Mahmoud M. Gamil & Soichirou Ueda & Akito Nakadomari & Keifa Vamba Konneh & Tomonobu Senjyu & Ashraf M. Hemeida & Mohammed Elsayed Lotfy, 2022. "Optimal Multi-Objective Power Scheduling of a Residential Microgrid Considering Renewable Sources and Demand Response Technique," Sustainability, MDPI, vol. 14(21), pages 1-20, October.

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